Homeostatic Control of Deep Sleep and Molecular Correlates of Sleep Pressure in Drosophila

  1. Budhaditya Chowdhury
  2. Lakshman Abhilash
  3. Antonio Ortega
  4. Sha Liu
  5. Orie T Shafer  Is a corresponding author
  1. City University of New York, United States
  2. VIB-KU Leuven Center for Brain & Disease Research, Belgium

Abstract

Homeostatic control of sleep is typically addressed through mechanical stimulation-induced forced wakefulness and the measurement of subsequent increases in sleep. A major confound attends this approach: biological responses to deprivation may reflect a direct response to the mechanical insult rather than to the loss of sleep. Similar confounds accompany all forms of sleep deprivation and represent a major challenge to the field. Here we describe a new paradigm for sleep deprivation in Drosophila that fully accounts for sleep-independent effects. Our results reveal that deep sleep states are the primary target of homeostatic control and establish the presence of multi-cycle sleep rebound following deprivation. Furthermore, we establish that specific deprivation of deep sleep state results in state-specific homeostatic rebound. Finally, by accounting for the molecular effects of mechanical stimulation during deprivation experiments, we show that serotonin levels track sleep pressure in the fly's central brain. Our results illustrate the critical need to control for sleep-independent effects of deprivation when examining the molecular correlates of sleep pressure and call for a critical reassessment of work that has not accounted for such non-specific effects.

Data availability

All Raw Data is available at Dryad.

The following data sets were generated

Article and author information

Author details

  1. Budhaditya Chowdhury

    Advanced Science Research Center, City University of New York, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Lakshman Abhilash

    The Advanced Science Research Center, City University of New York, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Antonio Ortega

    VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  4. Sha Liu

    VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  5. Orie T Shafer

    Advanced Science Research Center, City University of New York, New York, United States
    For correspondence
    oshafer@gc.cuny.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7177-743X

Funding

National Institute of Neurological Disorders and Stroke (R21NS131939)

  • Orie T Shafer

National Institute of Neurological Disorders and Stroke (R01NS077933)

  • Orie T Shafer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2023, Chowdhury et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,204
    views
  • 316
    downloads
  • 6
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Budhaditya Chowdhury
  2. Lakshman Abhilash
  3. Antonio Ortega
  4. Sha Liu
  5. Orie T Shafer
(2023)
Homeostatic Control of Deep Sleep and Molecular Correlates of Sleep Pressure in Drosophila
eLife 12:e91355.
https://doi.org/10.7554/eLife.91355

Share this article

https://doi.org/10.7554/eLife.91355

Further reading

    1. Neuroscience
    Gáspár Oláh, Rajmund Lákovics ... Gábor Tamás
    Research Article

    Human-specific cognitive abilities depend on information processing in the cerebral cortex, where the neurons are significantly larger and their processes longer and sparser compared to rodents. We found that, in synaptically connected layer 2/3 pyramidal cells (L2/3 PCs), the delay in signal propagation from soma to soma is similar in humans and rodents. To compensate for the longer processes of neurons, membrane potential changes in human axons and/or dendrites must propagate faster. Axonal and dendritic recordings show that the propagation speed of action potentials (APs) is similar in human and rat axons, but the forward propagation of excitatory postsynaptic potentials (EPSPs) and the backward propagation of APs are 26 and 47% faster in human dendrites, respectively. Experimentally-based detailed biophysical models have shown that the key factor responsible for the accelerated EPSP propagation in human cortical dendrites is the large conductance load imposed at the soma by the large basal dendritic tree. Additionally, larger dendritic diameters and differences in cable and ion channel properties in humans contribute to enhanced signal propagation. Our integrative experimental and modeling study provides new insights into the scaling rules that help maintain information processing speed albeit the large and sparse neurons in the human cortex.

    1. Neuroscience
    Zhujun Shao, Mengya Zhang, Qing Yu
    Research Article

    When holding visual information temporarily in working memory (WM), the neural representation of the memorandum is distributed across various cortical regions, including visual and frontal cortices. However, the role of stimulus representation in visual and frontal cortices during WM has been controversial. Here, we tested the hypothesis that stimulus representation persists in the frontal cortex to facilitate flexible control demands in WM. During functional MRI, participants flexibly switched between simple WM maintenance of visual stimulus or more complex rule-based categorization of maintained stimulus on a trial-by-trial basis. Our results demonstrated enhanced stimulus representation in the frontal cortex that tracked demands for active WM control and enhanced stimulus representation in the visual cortex that tracked demands for precise WM maintenance. This differential frontal stimulus representation traded off with the newly-generated category representation with varying control demands. Simulation using multi-module recurrent neural networks replicated human neural patterns when stimulus information was preserved for network readout. Altogether, these findings help reconcile the long-standing debate in WM research, and provide empirical and computational evidence that flexible stimulus representation in the frontal cortex during WM serves as a potential neural coding scheme to accommodate the ever-changing environment.